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io.github.goldbergyoni/test-coverage-mcp MCP Server

io.github.goldbergyoni/test-coverage-mcp

Make AI coding agents coverage-aware by analyzing LCOV files efficiently without wasting tokens

What is the io.github.goldbergyoni/test-coverage-mcp MCP server?

Test Coverage MCP is an MCP server that provides AI agents with instant access to test coverage data from LCOV files. It enables agents to check project and file-level coverage, track coverage changes within a session, and make coverage-informed coding decisions without parsing massive files or burning tokens.

This server solves coverage blindness for AI coding agents by offering token-efficient LCOV parsing and baseline tracking. Agents can query overall project coverage, check specific file coverage, and measure coverage impact of their changes during a session—all without keeping state in memory or wasting context on large file parsing.

How to install io.github.goldbergyoni/test-coverage-mcp

Copy-paste configuration for popular MCP clients.

transport: stdio
Config generated by PluginBench — verify against the source before use.
~/Library/Application Support/Claude/claude_desktop_config.json
{
  "mcpServers": {
    "test-coverage-mcp": {
      "command": "npx",
      "args": [
        "-y",
        "test-coverage-mcp"
      ]
    }
  }
}

Tools & capabilities

Tools this server exposes to the agent.

  • coverage_summary — Get overall project coverage percentages for lines and branches from an LCOV file
  • coverage_file_summary — Get coverage percentages for a specific file, including lines and branches coverage
  • start_recording — Record current coverage as a baseline for later comparison within the session
  • get_diff_since_start — Compare current coverage against the recorded baseline and return the percentage impact

Use cases

  • Check overall project test coverage before starting development work
  • Verify that code changes maintain or improve test coverage during a coding session
  • Track coverage impact of new features by comparing baseline coverage to current coverage
  • Identify which specific files have low coverage to prioritize testing efforts
  • Prevent coverage regressions by monitoring coverage changes as an agent writes code

io.github.goldbergyoni/test-coverage-mcp MCP server FAQ

What is the Test Coverage MCP server?

It's an MCP server that gives AI agents the ability to analyze test coverage from LCOV files efficiently. Instead of parsing massive LCOV files (which can exceed 10 MB), agents get compact JSON responses with coverage percentages in under 100 tokens.

Is it free?

Yes, Test Coverage MCP is open-source under the MIT license and available on npm.

How do I install it in Cursor?

Create or edit `.cursor/mcp.json` in your project root with the configuration: `{"mcpServers": {"test-coverage": {"command": "npx", "args": ["-y", "test-coverage-mcp"]}}}`

How do I install it in Claude Desktop?

Edit your Claude Desktop config file (`~/Library/Application Support/Claude/claude_desktop_config.json` on macOS or `%APPDATA%\Claude\claude_desktop_config.json` on Windows) and add the test-coverage server with the npx command.

Does it require authentication?

No, Test Coverage MCP does not require any authentication. It works directly with LCOV files on your local system.

What LCOV formats does it support?

It supports all standard LCOV file formats including files with summary sections, line-by-line data only, branch coverage data, and mixed formats within the same file.

README (reference)

Source of truth, from the repository.

Test Coverage MCP

npm version License: MIT Coverage CI Last Commit

Make your agents coverage-aware as they code for you

“Hey, I’m a coding agent. I just created flashy nifty feature… but oops, I downgraded the coverage 🤓. How could I know that?”

“Hey, I’m a testing agent. I was tasked to cover some code with testing, but how can I find which areas are not covered?😳”

Give your coding and testing agent eyes: MCP server that provides instant, reliable, token-efficient test coverage data for any programming language (LCOV based)

__

🚀 Just launched (November 2025) ! I spend great time these days on polishing this library. If you find this valuable, a ⭐ star helps signal to other developers that this project is worth their attention

The Problem

When AI coding agents work on your code without proper coverage tooling, they face three critical issues:

  1. Coverage Blindness - They can't see if their changes improved or regressed test coverage
  2. Token Waste - They burn thousands of tokens trying to parse massive LCOV files (some exceed 10 MB)
  3. Unreliable Scripts - They improvise custom parsing scripts that often fail or produce incorrect results

The Solution

This MCP server solves all three problems by providing:

  • Coverage Awareness - Agents can check coverage anytime with a simple tool call
  • Token Efficiency - Get coverage summaries in <100 tokens instead of thousands
  • Accuracy - Production-grade LCOV parsing that handles all format variations
  • Baseline Tracking - Measure coverage progress within a session without keeping state in memory

Test Coverage: This project maintains 95% test coverage and we're targeting 100% soon.

Two Main Workflows

1. Query Coverage Summary

Ask for overall project coverage or coverage for specific files:

// Get overall project coverage
coverage_summary({ lcovPath: "./coverage/lcov.info" });
// Returns: { linesCoveragePercentage: 87.5, branchesCoveragePercentage: 82.1 }

// Get coverage for specific files
coverage_file_summary({
  lcovPath: "./coverage/lcov.info",
  filePath: "src/utils/parser.ts",
});
// Returns: { path: "src/utils/parser.ts", linesCoveragePercentage: 92.0, branchesCoveragePercentage: 88.5 }

2. Baseline Tracking for Session Progress

Establish a baseline at session start, then measure your progress:

// At session start - record current coverage as baseline
start_recording({ lcovPath: "./coverage/lcov.info" });
// Returns: "Recording started"

// ... agent writes code and tests ...

// Check coverage impact
get_diff_since_start({ lcovPath: "./coverage/lcov.info" });
// Returns: { linesPercentageImpact: +2.3, branchesPercentageImpact: +1.8 }

Why baseline tracking? Without it, agents would need to keep initial coverage in their stateful memory throughout the session, consuming valuable context window space.

Installation

npm install -g test-coverage-mcp

Configuration

Add this MCP server to your AI coding tool's configuration:

Claude Desktop (Claude Code)

macOS: Edit ~/Library/Application Support/Claude/claude_desktop_config.json Windows: Edit %APPDATA%\Claude\claude_desktop_config.json

{
  "mcpServers": {
    "test-coverage": {
      "command": "npx",
      "args": ["-y", "test-coverage-mcp"]
    }
  }
}

After updating, restart Claude Desktop.

Cursor IDE

Create or edit .cursor/mcp.json in your project root:

{
  "mcpServers": {
    "test-coverage": {
      "command": "npx",
      "args": ["-y", "test-coverage-mcp"]
    }
  }
}

GitHub Copilot (VS Code)

Create or edit .vscode/mcp.json in your workspace:

{
  "servers": {
    "test-coverage": {
      "command": "npx",
      "args": ["-y", "test-coverage-mcp"]
    }
  }
}

Requires VS Code 1.99+ or Visual Studio 17.14+. Enterprise users need "MCP servers in Copilot" policy enabled.

Windsurf (Codeium IDE)

macOS: Edit ~/.codeium/windsurf/mcp_config.json Windows: Edit %APPDATA%\Codeium\Windsurf\mcp_config.json Linux: Edit ~/.codeium/windsurf/mcp_config.json

{
  "mcpServers": {
    "test-coverage": {
      "command": "npx",
      "args": ["-y", "test-coverage-mcp"]
    }
  }
}

Or use the GUI: Settings → Advanced Settings → Cascade → Add Server

Available Tools

coverage_summary

Get overall project coverage from an LCOV file.

Input:

{
  lcovPath?: string  // Optional. Defaults to "./coverage/lcov.info"
}

Output:

{
  linesCoveragePercentage: number,      // 0-100
  branchesCoveragePercentage: number    // 0-100
}

Example:

coverage_summary({ lcovPath: "./coverage/lcov.info" });
// { linesCoveragePercentage: 87.5, branchesCoveragePercentage: 82.1 }

coverage_file_summary

Get coverage for a specific file.

Input:

{
  lcovPath?: string,  // Optional. Defaults to "./coverage/lcov.info"
  filePath: string    // Required. Path to the file
}

Output:

{
  path: string,
  linesCoveragePercentage: number,      // 0-100
  branchesCoveragePercentage: number    // 0-100
}

Example:

coverage_file_summary({
  lcovPath: "./coverage/lcov.info",
  filePath: "src/utils/parser.ts",
});
// { path: "src/utils/parser.ts", linesCoveragePercentage: 92.0, branchesCoveragePercentage: 88.5 }

start_recording

Record current coverage as a baseline for later comparison.

Input:

{
  lcovPath: string; // Required. Path to LCOV file to record
}

Output:

"Recording started";

Example:

start_recording({ lcovPath: "./coverage/lcov.info" });
// "Recording started"

get_diff_since_start

Compare current coverage against the recorded baseline.

Input:

{
  lcovPath: string; // Required. Path to current LCOV file
}

Output:

{
  linesPercentageImpact: number,      // Positive = improvement, negative = regression
  branchesPercentageImpact: number    // Positive = improvement, negative = regression
}

Example:

get_diff_since_start({ lcovPath: "./coverage/lcov.info" });
// { linesPercentageImpact: +2.3, branchesPercentageImpact: +1.8 }

Usage Examples

Example 1: Check Coverage Before Starting Work

Agent: "Let me check the current test coverage before I start working"
[Uses coverage_summary tool]
Agent: "Current coverage is 87.5% lines and 82.1% branches. I'll aim to maintain or improve this."

Example 2: Track Coverage Impact During Development

Agent: "I'll record the baseline coverage first"
[Uses start_recording tool]

Agent: "Now I'll add the new authentication feature with tests"
[Writes code and tests]

Agent: "Let me check the coverage impact"
[Uses get_diff_since_start tool]
Agent: "Great! Coverage increased by 2.3% for lines and 1.8% for branches."

Example 3: Verify Specific File Coverage

Agent: "Let me check coverage for the file I just modified"
[Uses coverage_file_summary with filePath: "src/auth/validator.ts"]
Agent: "The validator.ts file now has 95% line coverage and 92% branch coverage."

How It Works

This MCP server:

  1. Parses LCOV files using a production-grade parser that handles all LCOV format variations
  2. Calculates coverage percentages for overall project or individual files
  3. Stores baselines in a temporary directory for session-based tracking
  4. Returns compact JSON responses that consume minimal tokens

LCOV Format Support

This server supports all standard LCOV file formats, including:

  • Files with summary sections (SF:, end_of_record)
  • Files with line-by-line data only (DA: entries)
  • Files with branch coverage data (BRDA:, BRF:, BRH:)
  • Mixed formats within the same file

Troubleshooting

"LCOV file not found"

  • Ensure you've run your test suite with coverage enabled first
  • Check that the path to your LCOV file is correct (relative paths are resolved from current working directory)
  • Default path is ./coverage/lcov.info

"No coverage data found for file"

  • Verify the file path matches exactly as it appears in the LCOV file
  • Some test frameworks use absolute paths, others use relative paths

"No baseline recording found"

  • You must call start_recording before calling get_diff_since_start
  • Baselines are stored in temporary storage and cleared when the system restarts

Development

# Install dependencies
npm install

# Build
npm run build

# Run tests (with coverage!)
npm test

# Run linter
npm run lint

# Test with MCP inspector
npm run inspect

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

License

MIT © Yoni Goldberg

Links

Improvement ideas

  • coverage_file_summary returns nested properties also declared as flat
  • Start recording overrides other sessions files
  • Improve record naming - setSessionBaseline, getDiffSinceBaseline

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